From web page to Anki deck in one click: a flashcard workflow that stays in your browser

glensum — Wed, 30 Sep 2026 02:09:21 +0000

If you use Anki seriously, you already know the workflow: read an article, spot a fact worth remembering, switch windows, paste it into a note template, reformat it, repeat. The reading and the card-making happen in two different worlds, and the friction quietly kills half the cards you intended to make.

This post walks through a workflow that keeps everything in the browser tab: select text, generate flashcards, review them, and write them straight into your Anki decks. It uses AnkiMate, a Chrome and Edge extension my team built — but the setup (AnkiConnect + a capture habit) works with other tools too, so most of this post applies even if you use something else.

The 60-second setup

Install the AnkiMate extension (also on Edge).
In desktop Anki, install the AnkiConnect add-on (code 2055492159) and restart Anki.
That's it. The extension talks to your local Anki over AnkiConnect — there is no account, no cloud sync step, no middleman.

The workflow: select → generate → review → write

Select any text on an article, lecture note, or documentation page (or use full page / PDF / YouTube transcript as input).
Right-click → Generate flashcards. A side panel opens with draft cards.
Edit or delete anything you don't like. Nothing is final here — every card is editable, removable, and draft-saved.
Pick a deck and hit Write to Anki. Cards land in your collection tagged and deduplicated.

The last step is the one that saves the most time. Cards are written directly into the deck you choose, deduplicated by content hash — and if the source page changed, the card gets updated instead of duplicated. No more discovering three near-identical cards about the same fact a month later.

Templates tuned by subject, not one generic prompt

A generic "make flashcards from this text" prompt produces generic cards. AnkiMate ships nine templates, each tuned for a subject:

Medicine (USMLE) — expects clinical detail, not trivia
GRE vocabulary — word, definition, usage
Language learning — front/back with context, plus a reversed-vocabulary variant
Law — element-based structure
Programming — concept and code-focused cards
List breakdown — turns enumerations into atomic cards (the classic "one fact per card" rule, enforced for you)
General — everything else

Eight templates are free. Pro adds Cloze deletions (fill-in-the-blank), which is the right format for definitions, dates, and anatomy.

Privacy: on-device AI by default, BYOK if you want more

This matters to us, so it's the design center: on-device AI handles generation by default, and your selected text never leaves the browser. If you want a stronger cloud model, you plug in your own API key — and then your text goes directly from the extension to that provider, not through our servers. We never see your selections, your cards, or your key. (We wrote up why this matters in more detail — most "AI readers" proxy every page you visit through their own backend.)

Pricing, honestly

Free, every day, no card required: 3 generations per day (roughly 45–90 cards), all 8 non-Pro templates, all input types, unlimited writes to Anki. For most students this is genuinely enough.
Pro · Lifetime $19.9 (launch price, $29.9 after): unlimited generations, batch generation of 20+ cards from long pages, and the Cloze template. One payment, no subscription — the price of two coffees for the tool you'll use every study session.

Honest limitations

Desktop Anki (with AnkiConnect) needs to be running when you write cards — AnkiMobile/AnkiDroid alone won't receive them.
Generation quality tracks source quality: a well-structured page produces great cards; a rambling forum thread needs more editing.
It makes cards, not understanding. Spaced repetition still requires you to actually do the reviews.

Try it

Install from the Chrome Web Store or Edge Add-ons, or read more at glenkit.com/ankimate. If you have questions about the AnkiConnect setup or template design, leave a comment — I reply to all of them.

How to summarize 2-hour videos and 50-page articles without leaving the browser tab

glensum — Tue, 29 Sep 2026 07:39:22 +0000

A 40-minute conference talk. A 90-minute podcast. A 12-minute tutorial that could have been a blog post. Most of what's valuable in a video is its content — and content can be read.

I've been building GlenSum, a browser extension that summarizes long videos and articles directly in the tab. This post covers the three working approaches to media summarization in a browser, the privacy trade-off most people don't notice they're making, and what "long content" actually means for an LLM.

Three ways to summarize a YouTube video (slowest to fastest)

1. The transcript, by hand

Every video with captions has a transcript: expand the description → Show transcript → select all → paste into any AI chat.

Cost: free
Time: 3–5 minutes of fiddly copying, and raw transcripts are messy — no punctuation, no speaker labels, timestamps everywhere
Best for: one-off use when you can't install anything

2. Paste the URL into an AI chat

Some assistants accept a YouTube URL directly and fetch the transcript themselves. Paste the link, ask for key points.

Cost: often limited by your plan's usage quota
Caveat: availability varies by model and region — and now the video passes through yet another service
Best for: occasional videos when you already pay for an assistant

3. A browser extension, one click

Extensions built for this read the transcript from the page you already have open and generate a structured summary in a side panel. The workflow becomes: open the video → click the extension → read the summary. No copying, no tab-switching.

The extras that matter: adjustable summary length, follow-up questions about the content ("what did they say about X?"), bilingual output when the talk isn't in your first language, and Markdown/PDF export so the summary lands in your notes.

The privacy trade-off most people miss

Here's the part that motivated building this in the first place. When you paste a URL or transcript into a hosted summarizer, your reading and watching history becomes someone's dataset. Article by article, video by video, a profile of what you consume accumulates on a server you don't control. That's a real cost that never shows up on the pricing page.

The alternative is BYOK — bring your own key:

You paste an API key from your own AI provider (OpenAI, Google, a local gateway, anything OpenAI-compatible) into the extension once.
The extension reads the page content in your browser and sends it directly to the provider you chose.
There is no middleman server. No account. No logs on my side, because there is no "my side" — the extension ships as static code, and the network calls go from your browser to your provider.

The trade-off is honest: you manage your own key, and free-tier users can still use built-in free models without one. But nobody in the middle ever sees what you read.

What "long" actually means for an LLM

Summarizing a 2-hour talk isn't just "paste transcript into prompt". A two-hour transcript is roughly 25,000–40,000 words — technically it may fit a modern context window, but quality degrades: the model skims, drops the middle, and blends sections together.

The approach that works is map-reduce over chunks:

Map: split the transcript (or article) into overlapping chunks at natural boundaries — chapters, speaker turns, section headings — and summarize each chunk separately.
Reduce: merge the chunk summaries into a final structured summary, keeping section-level detail instead of a mushy average.

This is also why page-native tools beat copy-paste: the extension already knows the page structure, so it can split at real boundaries instead of arbitrary token counts.

When a summary is the wrong tool

Summaries are ideal for inverted-pyramid content: talks, podcasts, news analysis, tutorials — where information density is low and predictable. They're poor substitutes for demonstration content: if someone is showing you how to do a three-point turn, no summary captures the steering.

A good rule: summarize first to decide whether to watch — not to avoid watching things worth watching.

Try it

GlenSum is free to install and works out of the box (built-in free models, or your own key for unlimited use):

🌐 Site & docs: glenkit.com/glensum
🧩 Edge Add-ons · Chrome Web Store

Questions about the architecture — especially around BYOK flows or chunking strategies for long transcripts — happy to answer in the comments.

DEV Community: glensum

From web page to Anki deck in one click: a flashcard workflow that stays in your browser

The 60-second setup

The workflow: select → generate → review → write

Templates tuned by subject, not one generic prompt

Privacy: on-device AI by default, BYOK if you want more

Pricing, honestly

Honest limitations

Try it

How to summarize 2-hour videos and 50-page articles without leaving the browser tab

Three ways to summarize a YouTube video (slowest to fastest)

1. The transcript, by hand

2. Paste the URL into an AI chat

3. A browser extension, one click

The privacy trade-off most people miss

What "long" actually means for an LLM

When a summary is the wrong tool

Try it